Many isolated rural communities are located in regions where there is an abundant and reliable supply of solar energy, but where the distance to the nearest power station is many tens or even hundreds of kilometre. It is therefore mainly in these areas that rural electrification is now being provided by PV generators. since Stand-Alone PV generator can offer the most cost-effective and reliable option for providing power needed in remote places. Accordingly these isolated rural canters are fitted with PV for lighting, a refrigerator, a television and socket to supply kitchen appliances

This mini review provides an overview of methods for manufacturing expanded graphite (EGT) and the use of its composites with metal oxides in the field of photodegradation of dyes. Dyes from textile manufacturing represent a significant environmental pollution problem in waterways worldwide, highlighting the need for environmentally friendly and efficient technologies to remove dyes from industrial and local wastewater. Photodegradation technologies offer a low-cost, sustainable solution with minimal secondary pollution. Carbon-based materials, such as expanded graphite, are advantageous in enhancing catalytic activity. Accordingly, this review will explore the different fabrication techniques of expanded graphite and summarize the recent d

          The research aims to determine the impact of Human Resources Accounting (HRA) on employee’s performance. The research’s problem was embodied in the lack of interest in HRA, which was reflected on the performance of employees in the Ministry of Education; the research adopted the descriptive-analytical approach, and the research community included the directors of departments and people at the headquarters of the Ministry of Education. The sample size was (224) individuals from the total community of 533. The questionnaire was adopted as the main tool for collecting data and information, as well as the interviews that were conducted by the researcher. In order to analyze t

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive ex

Arabic language processing with artificial intelligence has evolved significantly in the past decades, from traditional rule- and dictionary-based techniques, through statistical models to modern deep and transformer models. This review intends to present an overview of the most well-known Arabic models as well as datasets used for its training, and the main practical applications such as sentiment analysis, machine translation, speech recognition, and smart assistant. AI-based Arabic NLP has had good progress in the previous decades, from rule and dictionary-based approaches to statistical methods and deep transformative learning models nowadays. In addition to it, the most popular state-of-the-art models that are fine-tuned for the Arabi